疊代學習控制應用於六軸機器手臂之軌跡追蹤

現今國內各自動化相關產業所使用的工業機械手臂大部分都會搭配國外進口的控制器，為了增進國內機器人產業的競爭力，政府部門正積極推動國產控制器技術升級。本研究即致力於提升國產機器手臂之運動控制效能，以國內廠商上銀科技所生產的RA605六軸機器手臂搭配自行開發的PC-based控制器，達成高效能之軌跡追蹤控制。在設計控制演算法前，首先需對機器手臂建構運動學及動力學模型，由Lagrangian- equation及Newton-Euler equation兩種方法分別算出機械手臂動力學模型，在交互比對其正確性，接著加入馬達機械動力學模型可得到馬達力矩與機械手臂各軸角度之關係。在對機械手臂動力學模型做系統鑑別時，使用各軸獨立鑑別，並由最末軸逐一往回鑑別，以提高系統鑑別的安全性、準確性及降低運算複雜度。在機器手臂控制方面，使用計算力矩控制器結合PD回授控制來將系統非線性項消除以達到各軸獨立控制，接著使用數位擾動估測器來消除系統模型不準確性，改善計算力矩控制器因系統模型誤差導致控制精度不佳之問題，最後透過參考型或力矩型疊代學習控制器將重複性擾動誤差消除，以提升機械手臂控制效能。實驗結果顯示，在軸空間(joint space)中對5Hz以內的運動軌跡，各軸追蹤誤差之方均根值皆小於1467個編碼器計數值(即0.0497度)。

關鍵字

疊代學習；機器手臂；數位擾動估測器

並列摘要

Nowadays, most industrial robots used by domestic automation industries are equipped with controllers that are imported from abroad. In order to enhance the competitiveness of domestic robot industry, Taiwan government is promoting researches aiming at upgrading self-owned motion control technologies. Thus, this thesis addresses the motion control problems of the RA605 6-axis robot manipulator produced by HIWIN Technologies Corp. with the PC-based controller developed in this thesis to achieve high-precision trajectory tracking. Before we design the control algorithm, we build the kinematic and dynamic models for the robot manipulator. The dynamic model is established by using Lagrangian and Newton-Euler equations separately and their results are compared for cross validation. Furthermore, the dynamics of the joint motors are incorporated into the robot dynamic model to obtain the relation between motor torques and joint angles. To identify the parameters of the robot dynamic model, this thesis presents a method with security, accuracy, and computational efficiency by estimating the parameters joint by joint. For the aspect of robot control, this thesis proposes a method combing computed torque control, digital disturbance observer and iterative learning control (ILC). The ILC consists of two structures, which are torque-based ILC and reference-based ILC. Experimental results show that the root mean square tracking error of each joint for trajectories up to 5 Hz is less than 1467 encoder count value (i.e. 0.0497 degrees).

並列關鍵字

ILC ； Robot ； DDOB

參考文獻

[30] 蔡和軒, "七軸機器手臂最佳化路徑規劃與防止自我碰撞之研究," 碩士論文, 電控工程研究所, 國立交通大學, 新竹, 民國104年.

[1] J. J. Craig, Introduction to Robotics: Mechanics and Control, 3th ed.: Prentice Hall, 2005.

[2] R. Kelly, V. Santibanez, and A. Loria, Control of Robot Manipulators in Joint Space: Springer, 2005.

[6] M. M. Olsen and H. G. Petersen, "A new method for estimating parameters of a dynamic robot model," IEEE Transactions on Robotics and Automation, vol. 17, pp. 95-100, 2001.

[8] Y. Kim, J. Seok, I. Noh, and S. Won, "An adaptive disturbance observer for a two-link robot manipulator," in Control, Automation and Systems, 2008. ICCAS 2008. International Conference on, 2008, pp. 141-145.

國際替代計量

疊代學習控制應用於六軸機器手臂之軌跡追蹤

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